Product Finance Director, AI Products & GPU Investment Strategy

Mountain View · San Francisco · Seattle · 10+ years experience · Posted Oct 15, 2026

At a glance

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.

Databricks is looking for a Product Finance leader to scale its AI business with speed and financial rigor.
This role serves as the primary finance partner to AI Engineering and Product leaders, managing GPU supply and demand, product pricing, and unit economics.

Plan the GPU supply and demand that powers the business.
Establish a trusted, unified GPU demand plan across production inference, internal research, and new product bets so we invest ahead of growth without over-provisioning.
Drive capacity commitment and procurement strategies across major hyperscalers and emerging neoclouds, optimizing the mix of reserved, spot, and on-demand compute.
Lead revenue and margin analytics across the AI product portfolio, turning raw consumption telemetry into a clear read on customer adoption, retention, and product profitability.
Model the end-to-end unit economics of AI products before they ship, partnering with Product and Pricing to design consumption structures that drive adoption while protecting gross margin targets.
Partner with Engineering to define north star efficiency KPIs and translate them into committed engineering roadmaps.
Run tight financial operations, from auditable multi-cloud cost allocation to automated reporting, giving product and engineering leaders real-time visibility into their economic goals.
Design ROI and capital allocation frameworks to evaluate asymmetric bets—including frontier model research, internal compute clusters, and strategic partnerships.
Build, mentor, and scale a high-performing team of product finance analysts capable of operating at the intersection of deep technical infrastructure and commercial strategy.

10+ years of experience in Strategic/Product Finance, complemented by foundational training in Investment Banking, Private Equity, or Management Consulting.
Deep fluency in consumption-based business models, public cloud infrastructure costs, unit cost analysis, and gross margin optimization.
A proven track record of partnering directly with senior Engineering and Product executives to influence technical roadmaps and commercial pricing.
Demonstrated ability to build scalable financial systems from scratch and distill massive, complex telemetry data into models and recommendations leaders act on.
Experience building, leading, and developing high-output finance teams in fast-moving environments.

Direct experience operating in the AI and GPU economy, including familiarity with training/inference workloads, hyperscaler commitment structures, and neocloud economics.
Ownership of a multi-product P&L within a high-growth enterprise SaaS, PaaS, or data infrastructure company.
Hands-on proficiency with SQL, Python, or notebook environments to self-serve insights from raw usage data.